2 citations · 7 across the 17 of their papers we have counts for
8 papers · 1 filter
Neural Finite-State Machines for Surgical Phase Recognition
Hao Ding, Zhongpai Gao, Benjamin Planche +7
Surgical phase recognition (SPR) is crucial for applications in workflow optimization, performance evaluation, and real-time intervention guidance. However, current deep learning m…
ConceptAgent: LLM-Driven Precondition Grounding and Tree Search for Robust Task Planning and Execution
Corban Rivera, Grayson Byrd, William Paul +12
Robotic planning and execution in open-world environments is a complex problem due to the vast state spaces and high variability of task embodiment. Recent advances in perception a…
StraightTrack: Towards Mixed Reality Navigation System for Percutaneous K-wire Insertion
Han Zhang, Benjamin D. Killeen, Yu-Chun Ku +9
In percutaneous pelvic trauma surgery, accurate placement of Kirschner wires (K-wires) is crucial to ensure effective fracture fixation and avoid complications due to breaching the…
Towards Robust Algorithms for Surgical Phase Recognition via Digital Twin Representation
Hao Ding, Yuqian Zhang, Wenzheng Cheng +7
Surgical phase recognition (SPR) is an integral component of surgical data science, enabling high-level surgical analysis. End-to-end trained neural networks that predict surgical…
Seamless Augmented Reality Integration in Arthroscopy: A Pipeline for Articular Reconstruction and Guidance
Hongchao Shu, Mingxu Liu, Lalithkumar Seenivasan +5
Arthroscopy is a minimally invasive surgical procedure used to diagnose and treat joint problems. The clinical workflow of arthroscopy typically involves inserting an arthroscope i…
Towards Robust Surgical Automation via Digital Twin Representations from Foundation Models
Hao Ding, Lalithkumar Seenivasan, Hongchao Shu +7
Large language model-based (LLM) agents are emerging as a powerful enabler of robust embodied intelligence due to their capability of planning complex action sequences. Sound plann…
Performance and Non-adversarial Robustness of the Segment Anything Model 2 in Surgical Video Segmentation
Yiqing Shen, Hao Ding, Xinyuan Shao +1
Fully supervised deep learning (DL) models for surgical video segmentation have been shown to struggle with non-adversarial, real-world corruptions of image quality including smoke…
SegSTRONG-C: Segmenting Surgical Tools Robustly On Non-adversarial Generated Corruptions -- An EndoVis'24 Challenge
Hao Ding, Yuqian Zhang, Tuxun Lu +39
Surgical data science has seen rapid advancement with the excellent performance of end-to-end deep neural networks (DNNs). Despite their successes, DNNs have been proven susceptibl…